Start by clarifying requirements: input types, empty string, null handling, and case sensitivity. Then propose a simple linear scan solution, discussing time and space complexity. Finally, implement the function in a clean, readable manner and test with edge cases.
Pro tip: Mention that in production code, you'd leverage built-in library functions (e.g., Python's str.count) for simplicity and performance, but here you're demonstrating algorithmic thinking. Also, discuss how the solution scales for large strings or streaming data.
Ask about input constraints: can the string be empty? Is the character guaranteed to be a single character? How should null or invalid inputs be handled? Confirm case-sensitive matching.
Propose a linear scan: iterate through each character in the string, compare it to the target character, and increment a counter when they match. Mention that this is O(n) time and O(1) space.
Write clean code with meaningful variable names. Include input validation if necessary. For example, in Python: def count_char(s, c): return sum(1 for ch in s if ch == c).
Walk through examples: empty string, character not present, all characters match, and case sensitivity (e.g., 'A' vs 'a'). Verify the function returns correct counts.
Mention alternative approaches like using built-in functions (e.g., str.count) or regular expressions, and discuss their performance implications. Also, consider if the string is very large or streamed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem: split each string by spaces, compute the set of words unique to each string (i.e., words that appear in one string but not the other), and then concatenate the unique words from the first string followed by those from the second, preserving original order. Use a hash set for efficient lookups and a list to maintain order. Discuss time and space complexity.
Pro tip: Mention edge cases like empty strings, multiple spaces, and case sensitivity upfront, and ask if the definition of 'unique' means words that appear only in one string (not in both) or words that are distinct within each string. This shows attention to detail and avoids ambiguity.
Confirm the definition of 'unique' (words not present in the other string), handling of empty strings, multiple spaces, and case sensitivity. Ask if punctuation should be considered part of words.
Use sets to store words from each string for O(1) lookups, and lists to preserve the original order of unique words. Consider using an ordered set if available, but a list plus set is sufficient.
Split each string by spaces, iterate through the words, and for each word, check if it exists in the other string's set. If not, add it to the result list for that string, ensuring no duplicates within the same string.
Concatenate the list of unique words from the first string with that from the second string, and return the combined list.
State time complexity O(n+m) where n and m are the lengths of the strings, and space complexity O(n+m). Walk through a simple example to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.